Low-Voltage Substation Area Topology Recognition Method Based on AKNN Anomaly Detection and ADPC Clustering
The accurate record of topology information of the low-voltage station area is the basis for line loss analysis and three-phase imbalance control. Aiming at the problem of high cost and low efficiency of topology file investigation at present, a low-voltage substation area topology recognition metho...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
State Grid Energy Research Institute
2024-05-01
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| Series: | Zhongguo dianli |
| Subjects: | |
| Online Access: | https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202307030 |
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| Summary: | The accurate record of topology information of the low-voltage station area is the basis for line loss analysis and three-phase imbalance control. Aiming at the problem of high cost and low efficiency of topology file investigation at present, a low-voltage substation area topology recognition method is proposed based on adaptive k nearest neighbor (AKNN) anomaly detection and adaptive density peaks clustering (ADPC). The similarity of voltage series between users in the low-voltage substation area is measured using dynamic time warping (DTW), and the abnormal relationship between users and transformer is checked and corrected with the AKNN anomaly detection algorithm. After getting the right relationship, the ADPC algorithm is used to identify the phase for users in the substation area. Finally, the case study of the actual substation area proves that the proposed method can effectively realize the topology identification of the low-voltage substation area without human parameter setting, and has high applicability and accuracy. |
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| ISSN: | 1004-9649 |